Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto.

Afiliação

Lu X; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China. luxmnju@163.com.
Zheng G; Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, Nanjing 210023, China. zhengguang@nju.edu.cn.
Miller C; School of Environmental and Forest Sciences, University of Washington, Seattle, WA 98195, USA. cwm4@uw.edu.
Alvarado E; School of Environmental and Forest Sciences, University of Washington, Seattle, WA 98195, USA. alvarado@uw.edu.

Sensors (Basel) ; 17(9)2017 Sep 08.

Article em En | MEDLINE | ID: mdl-28885556

Assuntos

Biomassa; Ecologia/métodos; Florestas; Modelos Estatísticos; Tecnologia de Sensoriamento Remoto; Carbono/análise; China; Ecossistema

Palavras-chave

AGB; ALS; BEPS; NPP; process-based model

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Florestas / Modelos Estatísticos / Biomassa / Ecologia / Tecnologia de Sensoriamento Remoto Tipo de estudo: Prognostic_studies / Risk_factors_studies País/Região como assunto: Asia Idioma: En Ano de publicação: 2017 Tipo de documento: Article

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